WO2019100403A1 - 悬崖检测方法与机器人 - Google Patents

悬崖检测方法与机器人 Download PDF

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Publication number
WO2019100403A1
WO2019100403A1 PCT/CN2017/113202 CN2017113202W WO2019100403A1 WO 2019100403 A1 WO2019100403 A1 WO 2019100403A1 CN 2017113202 W CN2017113202 W CN 2017113202W WO 2019100403 A1 WO2019100403 A1 WO 2019100403A1
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WO
WIPO (PCT)
Prior art keywords
cliff
detection
ground
detecting
determining
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
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PCT/CN2017/113202
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English (en)
French (fr)
Inventor
郑勇
张立新
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shenzhen Water World Co Ltd
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Shenzhen Water World Co Ltd
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Publication date
Application filed by Shenzhen Water World Co Ltd filed Critical Shenzhen Water World Co Ltd
Priority to PCT/CN2017/113202 priority Critical patent/WO2019100403A1/zh
Publication of WO2019100403A1 publication Critical patent/WO2019100403A1/zh
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Classifications

    • AHUMAN NECESSITIES
    • A47FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
    • A47LDOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
    • A47L11/00Machines for cleaning floors, carpets, furniture, walls, or wall coverings
    • A47L11/24Floor-sweeping machines, motor-driven
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02Control of position or course in two dimensions

Definitions

  • the present invention relates to the field of robots, and more particularly to a cliff detection method and a robot.
  • the current cliff detection methods for indoor service robots generally use infrared signals for detection.
  • infrared signals are sensitive to the color information of the ground.
  • the detection signal value of the black ground is significantly lower than the detection signal of the white ground at the same distance.
  • the robot cannot detect the ground state information such as the ground color and the ground material, it is impossible to dynamically set the limit conditions of the cliff detection based on the ground state information, which may cause misjudgment.
  • the indoor service robot will judge the result of the infrared signal, and judge the dark carpet as a cliff and refuse to continue service; for example, in the process of working in the home environment, When encountering some special circumstances, such as detecting the reflective performance of the ground is better, the cliff judgment may be inaccurate, and the indoor service robot may fall.
  • the main object of the present invention is to provide a cliff detecting method, which aims to solve the technical problem that the existing robot cannot dynamically set the limit condition of the cliff detection according to the ground state information, resulting in inaccurate judgment.
  • the present invention provides a cliff detection method, including:
  • the present invention also provides a robot, including:
  • a monitoring module configured to monitor state change information of the ground during the movement; ⁇ 0 2019/100403 ⁇ (:17 ⁇ 2017/113202
  • a setting module configured to set a limit condition of the cliff detection according to the state change information
  • a judging module configured to determine, according to the qualification condition and a preset rule corresponding to the qualification condition, whether the ground is a cliff.
  • the present invention monitors the state change information dynamics of the ground during the movement process by the robot, and then dynamically sets the limit conditions of the cliff detection according to the state change information of the ground, taking into account the interference factors affecting the cliff detection, Dynamically adjust the cliff judgment criteria suitable for the current ground conditions, and refine the qualification conditions of cliff detection under different ground conditions to improve the accuracy of the robot to judge the cliff and reduce misjudgment.
  • FIG. 1 is a schematic flow chart of a cliff detecting method according to an embodiment of the present invention
  • step 32 of still another embodiment of the present invention is a schematic flow chart of step 32 of still another embodiment of the present invention.
  • step 32 of still another embodiment of the present invention is a schematic flow chart of step 32 of still another embodiment of the present invention.
  • FIG. 6 is a schematic diagram showing an optimization process of a cliff detecting method according to still another embodiment of the present invention.
  • FIG. 7 is a schematic diagram of a re-optimization process of a cliff detecting method according to still another embodiment of the present invention.
  • FIG. 8 is a schematic structural view of a robot according to an embodiment of the present invention.
  • FIG. 9 is a schematic structural diagram of a setting module according to another embodiment of the present invention.
  • FIG. 10 is a schematic structural diagram of a determining module according to another embodiment of the present invention.
  • FIG. 11 is a schematic structural diagram of a setting module according to still another embodiment of the present invention.
  • FIG. 12 is a schematic structural diagram of a determining module according to still another embodiment of the present invention.
  • FIG. 13 is a schematic diagram showing an optimized structure of a robot according to still another embodiment of the present invention.
  • FIG. 14 is a schematic diagram showing a re-optimization structure of a robot according to still another embodiment of the present invention.
  • FIG. 15 is a schematic flow chart of a startup unit according to still another embodiment of the present invention.
  • 16 is a schematic flow chart of a startup unit according to still another embodiment of the present invention. ⁇ 0 2019/100403 ⁇ (:17 ⁇ 2017/113202
  • a cliff detecting method includes:
  • the state change information in this step includes: a change in the ground color, a change in the intensity of the ground reflected light, a change in the ground material, and the like that affect the detection of the infrared sensor cliff.
  • an indoor sweeping robot equipped with an infrared cliff sensor at the bottom of the fuselage head is taken as an example, and the robot monitors the state change information of the ground in real time during the moving process.
  • the infrared detection signal sent by the infrared cliff sensor of the embodiment is sensitive to the ground state change information such as the ground color.
  • the limit condition of the cliff detection is dynamically set according to different state change information of the ground to suit the current ground state. Infrared cliff detection standards.
  • the limiting condition of this embodiment is preset, for example, matching the qualification conditions corresponding to different colors by experiments in advance.
  • the infrared radiation signal is sensitive to the color information of the ground, and the signal value of detecting the black ground is significantly lower than the signal value of the white ground of the same distance; when the ground state change information is detected to change from white to black, then the black color is selected.
  • the interference factors affecting the cliff detection are taken into account, and the cliff judgment criteria suitable for the current ground condition of the robot are dynamically adjusted to improve the accuracy of the judgment cliff and reduce misjudgment.
  • [0037] 83 determining whether the ground is a cliff according to the above-mentioned qualification condition and a preset rule corresponding to the above-described qualification condition.
  • the matching preset rule is correspondingly matched according to the qualification condition, so as to further improve the accuracy of the judgment cliff and reduce the false judgment.
  • the ground color change information is used as a limiting condition and the ground reflected light intensity change information is used as a qualification condition, and the preset rule for judging the cliff is different.
  • a method for detecting a cliff wherein the state change information includes a change in reflected light intensity, and the step 32 includes: ⁇ 0 2019/100403 ⁇ (:17 ⁇ 2017/113202
  • [0040] 820 Monitor an intensity difference between the reflected light intensity of the first detection ground and the preset standard reflected light intensity.
  • the ground reflected light intensity of the embodiment affects the infrared sensor to detect the cliff by detecting the amount of change of the infrared radiant energy.
  • the infrared detection signal with a large reflected light intensity is significantly larger than the reflected light intensity of the same distance. signal.
  • the intensity of the reflected light on the ground is related to the surface topography of the ground, the material and the distance between the ground and the detector.
  • the preset standard reflected light intensity is set according to the different materials of the flat surface state, and the reflected light passing through the first detecting ground
  • the error range of the intensity and the preset standard reflected light intensity can be used to obtain the ground material matching information, and the ground state change information is judged by further monitoring the intensity difference between the reflected light intensity of the first detecting ground and the preset standard reflected light intensity.
  • the infrared detection threshold corresponding to the reflected light intensity of the embodiment is determined by an experimentally determined level, and the error fluctuation in the same level range, such as the difference fluctuation of the small amplitude of the ground, does not need to be changed. Qualifications; When the difference crosses the level, the infrared detection threshold needs to be changed.
  • the determination error of detecting the cliff under different reflected light intensities is removed as much as possible by changing the infrared detection threshold.
  • the infrared detection cliff determines the presence or absence of a cliff by comparing the intensity of the feedback signal of the transmitted wave.
  • a cliff detecting method according to another embodiment of the present invention, the foregoing step 33 includes:
  • the first infrared detection signal is an infrared radiation energy signal sent by the infrared cliff sensor.
  • the first feedback signal refers to a radiation signal that the infrared radiation signal returns to the infrared cliff sensor after hitting the obstacle
  • the first detection threshold is determined by specifying the feedback signal intensity of the infrared radiation energy when there is no cliff under the ground reflected light intensity, and when the first feedback signal is smaller than the first detection threshold, it is determined as a cliff. When the first feedback signal is not less than the first detection threshold, the determination is safe.
  • the state change information includes a color change
  • step 32 includes:
  • the infrared detection thresholds on the cliff-free ground of different pure colors are matched in advance by experiments, so that the infrared cliff sensor dynamically sets the infrared detection threshold according to different ground colors when detecting the cliff, so as to eliminate infrared radiation energy of different colors. Error caused by different signal absorption rates.
  • the second detection threshold is determined by the intensity of the infrared radiation energy feedback signal when the ground is in a specified color, and there is no cliff.
  • the received feedback signal is smaller than the second infrared detection, it is determined to be a cliff.
  • the state change information includes a color change
  • the step 33 further includes:
  • the infrared cliff sensor detection principle of 334 to 337 in the present embodiment is different from the other embodiment of the present invention except that the infrared line detection threshold and the preset rule for determining the cliff method are different.
  • the absorption rate of the infrared radiation energy by the color is largely different, and the ground material and its shape ⁇ 0 2019/100403 ⁇ (:17 ⁇ 2017/113202
  • this embodiment further determines whether it is a cliff or not, and improves the accuracy by means of stepwise judgment.
  • the second feedback signal when the second feedback signal is smaller than the second detection threshold, it cannot be directly determined as a cliff.
  • a white long-haired carpet is set to a second detection threshold according to white, but the long-haired carpet is scattered to the infrared radiation. Color and absorption, leading to false judgments appearing on the cliff.
  • the second feedback signal is smaller than the second detection threshold, and the preset level is divided into the determined cliff level and the pending cliff level. For example, the feedback time is long, and the feedback signal energy is small, in order to determine the cliff level; the feedback time is short, and the feedback signal energy is small, and the cliff level is to be determined.
  • the method includes:
  • the auxiliary detection in this step includes detecting the physical height of the ground and the robot body, the surface material appearance and the like, and the auxiliary judgment means, so as to infer the reliability of the conclusion from multiple dimensions, and further improve the accuracy.
  • the pre-judgment range in this step includes: a judgment conclusion directly obtained according to the detection result of the auxiliary detection.
  • the surface of the second detecting ground is detected as a long-haired white wool carpet, which is 400 to 500 smaller than the standard flat white ground, and the smaller 400 to 500 is just long hair.
  • the above difference is considered to be within the pre-judgment range, not the cliff; otherwise, it is the cliff.
  • a cliff detecting method includes:
  • the physical height of the detection ground and the robot body is obtained by an auxiliary robot arm or an ultrasonic detector, and the embodiment is preferably one or more ultrasonic detectors disposed at the bottom of the robot body to obtain a height difference auxiliary detection signal.
  • the cliff detecting method of the second embodiment of the present invention, the step 3362, further includes: ⁇ 0 2019/100403 ⁇ (:17 ⁇ 2017/113202
  • the material detector disposed at the end of the auxiliary robot arm preferably acquires the surface material of the second detecting ground.
  • a robot according to an embodiment of the present invention includes:
  • the monitoring module 1 is configured to monitor state change information of the ground during the movement of the robot.
  • the state change information of the embodiment includes: a change in the color of the ground, a change in the intensity of the reflected light on the ground, a change in the ground material, and the like, which affect the detection of the infrared sensor cliff.
  • an indoor sweeping robot equipped with an infrared cliff sensor at the bottom of the fuselage head is taken as an example, and the robot monitors the state change information of the ground in real time during the moving process.
  • the setting module 2 is configured to set a qualification condition of the cliff detection according to the state change information.
  • the infrared detection signal sent by the infrared cliff sensor of the embodiment is sensitive to the ground state change information such as the ground color.
  • the limit condition of the cliff detection is dynamically set according to different state change information of the ground to suit the current ground state. Infrared cliff detection standards.
  • the limiting condition of this embodiment is preset, for example, matching the qualification conditions corresponding to different colors by experiments in advance.
  • the infrared radiation signal is sensitive to the color information of the ground, and the signal value of detecting the black ground is significantly lower than the signal value of the white ground of the same distance; when the ground state change information is detected to change from white to black, then the black color is selected.
  • the interference factors affecting the cliff detection are taken into account, and the cliff judgment criteria suitable for the current ground condition of the robot are dynamically adjusted to improve the accuracy of the judgment cliff and reduce misjudgment.
  • the determining module 3 is configured to determine whether the ground is a cliff according to the foregoing limiting condition and a preset rule corresponding to the qualifying condition.
  • the matching preset rule is correspondingly matched according to the qualified condition, so as to further improve the accuracy of the judgment cliff and reduce the false positive.
  • the ground color change information is used as a limiting condition and the ground reflected light intensity change information is used as a qualification condition, and the preset rule for judging the cliff is different.
  • the state change information includes a change in reflected light intensity
  • the setting module 2 includes:
  • the first monitoring unit 20 is configured to monitor an intensity difference between the reflected light intensity of the first detecting ground and the preset standard reflected light intensity.
  • the ground reflected light intensity of the embodiment may affect the infrared sensor to detect the cliff by detecting the amount of change of the infrared radiant energy.
  • the infrared detection signal with a large reflected light intensity is significantly larger than the reflected light intensity of the same distance. signal.
  • the reflected light intensity of the ground is related to the surface topography of the ground, the material, and the distance between the ground and the detector.
  • the preset standard reflected light intensity is set according to different materials of the flat surface state, and the reflection through the first detecting ground is The error range of the light intensity and the preset standard reflected light intensity can be used to obtain the ground material matching information, and the ground state change information is judged by further monitoring the intensity difference between the reflected light intensity of the first detecting ground and the preset standard reflected light intensity.
  • the first determining unit 21 is configured to determine, according to the intensity difference value, whether the foregoing limiting condition needs to be changed.
  • the infrared detection threshold corresponding to the reflected light intensity of the embodiment is determined by an experimentally determined level, and the error fluctuation in the same level range, such as the difference fluctuation of the small amplitude of the ground, does not need to be changed. Qualifications; When the difference crosses the level, the infrared detection threshold needs to be changed.
  • the calling unit 22 is configured to: if the determination is yes, invoke the first detection threshold corresponding to the reflected light intensity.
  • the infrared detection cliff determines whether there is a cliff by comparing the intensity of the feedback signal of the transmitted wave.
  • the determining module 3 includes:
  • the first sending unit 30 is configured to send the first infrared detection signal to the first detection ground.
  • the first infrared detection signal is an infrared radiation energy signal sent by the infrared cliff sensor.
  • the first receiving unit 31 is configured to receive the first feedback signal of the first infrared detection signal.
  • the first feedback signal refers to a radiation signal that the infrared radiation signal returns to the infrared cliff sensor after hitting the obstacle
  • the second determining unit 32 is configured to determine whether the first feedback signal is smaller than the first detection threshold.
  • the first detection threshold is determined by specifying the feedback signal intensity of the infrared radiation energy when there is no cliff under the ground reflected light intensity, and when the first feedback signal is smaller than the first detection threshold, it is determined as a cliff. When the first feedback signal is not less than the first detection threshold, the determination is safe.
  • the first determining unit 33 is configured to determine that the first detecting ground is a cliff if the first feedback signal is smaller than the first detection threshold.
  • the state change information includes a color change, ⁇ 0 2019/100403 ⁇ (:17 ⁇ 2017/113202
  • the second monitoring unit 24 is configured to monitor the color of the second detection ground.
  • the third determining unit 25 is configured to determine whether there is a second detection threshold that matches the color.
  • the infrared detection thresholds on the cliff-free ground of different pure colors are matched in advance by experiments, so that the infrared cliff sensor dynamically sets the infrared detection threshold according to different ground colors when detecting the cliff, so as to eliminate infrared radiation energy of different colors. Error caused by different signal absorption rates.
  • the setting unit 26 is configured to, if present, set a second limiting condition that is smaller than the second detection threshold value for cliff detection.
  • the second detection threshold is determined by the intensity of the infrared radiation energy feedback signal when the ground is in the specified color, and there is no cliff.
  • the received feedback signal is smaller than the second infrared detection, it is determined as a cliff.
  • the state change information includes a color change
  • the determining module 3 further includes:
  • the second sending unit 34 is configured to send a second infrared detection signal to the second detection ground.
  • the second receiving unit 35 is configured to receive a second feedback signal of the second infrared detection signal.
  • the fourth determining unit 36 is configured to determine whether the second feedback signal is smaller than the second detection threshold.
  • the second determining unit 37 is configured to determine that the robot continues to move forward if the second feedback signal is not smaller than the second detection threshold.
  • the infrared cliff sensor detection principle in this embodiment is the same as that of another embodiment of the present invention, except that the infrared detection threshold and the preset rule for determining the cliff method are different.
  • the judging module 3 of the robot includes:
  • the fifth determining unit 360 is configured to determine, according to the second detection threshold that the second feedback signal is less than the second detection threshold, a preset level corresponding to the second feedback signal, where the preset level includes determining a cliff level and a pending cliff level.
  • the second feedback signal is smaller than the second detection threshold, and cannot be directly determined as a cliff, for example, a white long-haired carpet
  • the second detection threshold is set according to white, but the long-haired carpet is scattered to the infrared radiation. Color and absorption, leading to false judgments appearing on the cliff.
  • the second feedback signal is smaller than the second detection threshold, and the preset level is divided into the determined cliff level and the pending cliff level. For example, the feedback time is long, and the feedback signal energy is small, in order to determine the cliff level; the feedback time is short, and the feedback signal energy is small, and the cliff level is to be determined.
  • the third determining unit 361 is configured to determine that the second detecting ground is a cliff if the cliff level is determined.
  • the determining module 3 of the robot includes:
  • the starting unit 362 is configured to start the auxiliary detection if the cliff level is to be determined.
  • the auxiliary detection in this embodiment includes detecting the physical height of the ground and the robot body, and the auxiliary judgment means of the ground material shape, so as to infer the reliability of the conclusion from multiple dimensions, and further improve the accuracy.
  • the sixth determining unit 363 is configured to determine, according to the detection result of the auxiliary detection, whether the difference is within a predetermined range.
  • the pre-judgment range in this embodiment includes: a judgment conclusion directly obtained according to the detection result of the auxiliary detection.
  • the surface of the second detecting ground is detected as a long-haired white wool carpet, which is 400 to 500 smaller than the standard flat white ground, and the smaller 400 to 500 is just long hair.
  • the above difference is considered to be within the pre-judgment range, not the cliff; otherwise, it is the cliff.
  • the fourth determining unit 364 is configured to determine that the second detecting ground is a cliff if the difference is not within the pre-judgment range.
  • the starting unit 362 includes:
  • the first detecting subunit 3620 is configured to detect, by using an ultrasonic detector, a height difference between the ground currently located and the second detecting ground.
  • the physical height of the detection ground and the robot body is obtained by an auxiliary robot arm or an ultrasonic detector.
  • one or more ultrasonic detectors disposed at the bottom of the robot body preferably obtain a height difference auxiliary detection signal.
  • the starting unit 362 further includes:
  • the second detecting subunit 3621 is configured to detect a surface material condition of the second detecting ground by using a material detector.
  • the material detector disposed at the end of the auxiliary robot arm preferably acquires the surface material of the second detecting ground.
  • the robot dynamically sets the limit condition of the cliff detection by monitoring the state change information of the ground, and takes into account the interference factors affecting the cliff detection, and dynamically adjusts the cliff judgment standard suitable for the current ground condition of the robot.
  • the qualification conditions of cliff detection under different ground conditions are used to improve the accuracy of the robot to judge the cliff and reduce misjudgment.

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Abstract

一种悬崖检测方法,包括:监测机器人移动过程中的所处地面的状态变化信息(S1);根据状态变化信息设置悬崖检测的限定条件(S2);根据限定条件以及与限定条件对应的预设规则判断探测地面是否为悬崖(S3)。通过将影响悬崖检测的干扰因素考虑在内,动态调控适合当前地面状况的悬崖判断标准,减少误判。还涉及一种机器人。

Description

\¥0 2019/100403 卩(:17 謂17/113202
1
悬崖捡测方法与机器人
技术领域
[0001] 本发明涉及到机器人领域, 特别是涉及到悬崖检测方法与机器人。
背景技术
[0002] 目前的室内服务机器人的悬崖检测方法普遍都是使用红外信号进行检测, 然 而红外信号对地面的颜色信息比较敏感, 比如黑色地面的检测信号值明显低于 同距离的白色地面的检测信号。 但由于机器人无法探测地面颜色、 地面材质等 地面状态信息, 更无法根据地面状态信息动态设置悬崖检测的限定条件, 导致 容易发生误判。 比如, 无悬崖的白色地面上铺设薄层深色地毯, 则室内服务机 器人会根据红外信号检测结果, 将深色地毯判定为悬崖而拒绝继续服务; 再比 如, 机器人在家庭环境工作的过程中, 遇到一些特殊的环境, 比如探测地面的 反光性能比较好, 则可能发生悬崖判断不准确, 发生室内服务机器人跌落的现 象。
[0003] 因此, 现有技术还有待改进。
技术问题
[0004] 本发明的主要目的为提供一种悬崖检测方法, 旨在解决现有机器人不能根据 地面状态信息动态设置悬崖检测的限定条件而导致判断不准确的技术问题。 问题的解决方案
技术解决方案
[0005] 本发明提出一种悬崖检测方法, 包括:
[0006] 监测机器人移动过程中的地面的状态变化信息;
[0007] 根据所述状态变化信息设置悬崖检测的限定条件;
[0008] 根据所述限定条件以及与所述限定条件对应的预设规则判断探测地面是否为悬
[0009] 本发明还提供了一种机器人, 包括:
[0010] 监测模块, 用于监测移动过程中的地面的状态变化信息; \¥0 2019/100403 卩(:17 \2017/113202
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[0011] 设置模块, 用于根据所述状态变化信息设置悬崖检测的限定条件;
[0012] 判断模块, 用于根据所述限定条件以及与所述限定条件对应的预设规则判断探 测地面是否为悬崖。
发明的有益效果
有益效果
[0013] 本发明有益技术效果: 本发明通过机器人监测移动过程中地面的状态变化信 息动态, 进而根据地面的状态变化信息动态设置悬崖检测的限定条件, 将影响 悬崖检测的干扰因素考虑在内, 动态调控适合当前地面状况的悬崖判断标准, 细化不同地面状态下的悬崖检测的限定条件, 以提高机器人判断悬崖的准确度 , 减少误判。
对附图的简要说明
附图说明
[0014] 图 1本发明一实施例的悬崖检测方法的流程示意图;
[0015] 图 2本发明另一实施例的步骤 32的流程示意图;
[0016] 图 3本发明另一实施例的步骤 33的流程示意图;
[0017] 图 4本发明再一实施例的步骤 32的流程示意图;
[0018] 图 5本发明再一实施例的步骤 32的流程示意图;
[0019] 图 6本发明再一实施例的悬崖检测方法的优化流程示意图;
[0020] 图 7本发明再一实施例的悬崖检测方法的再优化流程示意图;
[0021] 图 8本发明一实施例的机器人的结构示意图;
[0022] 图 9本发明另一实施例的设置模块的结构示意图;
[0023] 图 10本发明另一实施例的判断模块的结构示意图;
[0024] 图 11本发明再一实施例的设置模块的结构示意图;
[0025] 图 12本发明再一实施例的判断模块的结构示意图;
[0026] 图 13本发明再一实施例的机器人的优化结构示意图;
[0027] 图 14本发明再一实施例的机器人的再优化结构示意图;
[0028] 图 15本发明又一实施例的启动单元的流程示意图;
[0029] 图 16本发明又二实施例的启动单元的流程示意图。 \¥0 2019/100403 卩(:17 \2017/113202
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[0030] 本发明目的的实现、 功能特点及优点将结合实施例, 参照附图做进一步说明。
实施该发明的最佳实施例
本发明的最佳实施方式
[0031] 应当理解, 此处所描述的具体实施例仅仅用以解释本发明, 并不用于限定本发 明。
[0032] 参照图 1, 本发明一实施例的悬崖检测方法, 包括:
[0033] 81: 监测机器人移动过程中的地面的状态变化信息。
[0034] 本步骤中的状态变化信息包括: 地面颜色的变化、 地面反射光强度变化、 地面 材质的变化等影响红外传感器悬崖检测的信息。 本实施例以机身头部底壳处安 装红外悬崖传感器的室内扫地机器人为例, 机器人在移动过程中实时监测地面 的状态变化信息。
[0035] 82: 根据上述状态变化信息设置悬崖检测的限定条件。
[0036] 本实施例的红外悬崖传感器发送的红外检测信号对地面颜色等地面状态变化信 息比较敏感, 本实施例根据地面不同的状态变化信息, 动态设置悬崖检测的限 定条件, 以适合当前地面状态的红外线悬崖检测标准。 本实施例的限定条件为 预设的, 比如预先通过实验匹配不同颜色所对应的限定条件。 举例地, 红外线 的辐射信号对地面的颜色信息比较敏感, 检测黑色地面的信号值明显低于同距 离的白色地面的信号值; 当检测到地面状态变化信息由白色变为黑色, 则选择 黑色所对应的悬崖检测的限定条件本实施例将影响悬崖检测的干扰因素考虑在 内, 动态调控适合机器人当前地面状况的悬崖判断标准, 以提高判断悬崖的准 确度, 减少误判。
[0037] 83: 根据上述限定条件以及与上述限定条件对应的预设规则判断探测地面是否 为悬崖。
[0038] 本实施例中根据限定条件对应匹配预设规则, 以进一步提高判断悬崖的准确度 , 减少误判。 比如以地面颜色变化信息作为限定条件与以地面反射光强度变化 信息作为限定条件, 其所对应的判断悬崖的预设规则不同。
[0039] 参照图 2, 本发明另一实施例的悬崖检测方法, 上述状态变化信息包括反射光 强度变化, 上述步骤32, 包括: \¥0 2019/100403 卩(:17 \2017/113202
4
[0040] 820: 监测第一探测地面的反射光强度与预设标准反射光强度的强度差值。
[0041] 本实施例的地面反射光强度会影响红外传感器通过检测红外辐射能的变化量来 检测悬崖的判断, 比如, 反射光强度大的红外检测信号明显大于同距离的反射 光强度小的检测信号。 地面的反射光强度与地面的表面形貌、 材质以及地面与 检测器的距离等有关, 本步骤中预设标准反射光强度依据平坦表面状态的不同 材质而设, 通过第一探测地面的反射光强度与预设标准反射光强度的误差范围 可获知地面材质匹配信息, 并通过进一步监测第一探测地面的反射光强度与预 设标准反射光强度的强度差值, 来判断地面状态变化信息。
[0042] 821: 根据上述强度差值判断是否需要更改上述限定条件。
[0043] 本实施例的反射光强度对应的红外线检测阈值会预先经过实验确定等级划分, 同等级范围内的误差波动, 比如地面的小幅度的凹凸不平带来的差值波动等, 则无需更改限定条件; 差值跨越等级时, 则需要变更红外线检测阈值。
[0044] 822: 若判定是, 调用上述反射光强度对应的第一检测阈值。
[0045] 通过改变红外线检测阈值尽可能的除去不同反射光强度下检测悬崖的判断误差 。 红外线检测悬崖通过比较发射波的反馈信号的强度, 来判断是否有悬崖。 本 实施例中的第一、 第二等仅为便于描述, 不用于限定, 本发明其他处的类似书 写, 作用相同, 不赘述。
[0046] 参照图 3, 本发明另一实施例的悬崖检测方法, 上述步骤33, 包括:
[0047] 830: 向上述第一探测地面发送第一红外检测信号。
[0048] 本实施例中第一红外检测信号为红外悬崖传感器发送的红外辐射能信号。
[0049] 831: 接收上述第一红外检测信号的第一反馈信号。
[0050] 第一反馈信号指红外辐射信号碰到障碍物后返回到红外悬崖传感器的辐射信号
[0051] 832: 判断上述第一反馈信号是否小于上述第一检测阈值。
[0052] 本实施例中以指定地面反射光强度下, 无悬崖时的红外辐射能量的反馈信号强 度来确定第一检测阈值, 当第一反馈信号小于第一检测阈值时, 判定为悬崖, 若第一反馈信号不小于第一检测阈值时, 判定安全。
[0053] 833: 若上述第一反馈信号小于上述第一检测阈值, 则判定上述第一探测地面 \¥0 2019/100403 卩(:17 \2017/113202
5 为悬崖。
[0054] 参照图 4, 本发明再一实施例的悬崖检测方法, 上述状态变化信息包括颜色变 化, 步骤 32, 包括:
[0055] 824: 监测第二探测地面的颜色。
[0056] 不同颜色对红外辐射光的吸收程度不同, 由于深颜色对红外辐射光的吸收程度 较高, 导致地面为黑色时, 红外辐射能信号的反馈信号值明显偏低, 甚至接收 不到反馈信号, 所以地面颜色对红外传感器检测悬崖的判断结果存在干扰。
[0057] 825: 判断是否存在与上述颜色匹配的第二检测阈值。
[0058] 本实施例预先通过实验匹配在不同纯颜色的无悬崖地面上的红外线检测阈值, 以便红外悬崖传感器在检测悬崖时根据不同地面颜色动态设置红外线检测阈值 , 以消除不同颜色对红外辐射能信号吸收率不同而导致的误差。
[0059] 826: 若存在, 则根据上述第二检测阈值设定悬崖检测的限定条件。
[0060] 本实施例中以指定颜色地面, 无悬崖时的红外辐射能量反馈信号强度来确定第 二检测阈值, 当接收的反馈信号小于第二红外线检测时, 判定为悬崖。
[0061] 参照图 5 , 本发明再一实施例的悬崖检测方法, 上述状态变化信息包括颜色变 化, 上述步骤33 , 还包括:
[0062] 834: 向上述第二探测地面发送第二红外检测信号。
[0063] 835: 接收上述第二红外检测信号的第二反馈信号。
[0064] 836: 判断上述第二反馈信号是否小于上述第二检测阈值。
[0065] 837: 若上述第二反馈信号不小于上述第二检测阈值, 则判定机器人继续向前 移动。
[0066] 本实施中的 334至337的红外悬崖传感器检测原理同本发明另一实施例, 只是红 外线检测阈值及其确定悬崖方法的预设规则不同。
[0067] 参照图 6 , 进一步地, 本发明再一实施例的悬崖检测方法中步骤 336之后, 包括
[0068] 8360: 若上述第二反馈信号小于上述第二检测阈值, 则判断上述第二反馈信号 对应的预设等级, 上述预设等级包括确定悬崖等级和待定悬崖等级。
[0069] 本实施例由于颜色对红外辐射能量的吸收率由较大差别、 而且地面材质及其形 \¥0 2019/100403 卩(:17 \2017/113202
6 貌也会同时影响地面对红外辐射能量的吸收率, 因此, 本实施例通过逐步判处 的方式, 进一步判定是否为悬崖, 提高准确度。 本实施例当第二反馈信号小于 第二检测阈值, 并不能直接断定为悬崖, 比如, 白色的长毛状地毯, 按照白色 设置第二检测阈值, 但长毛状的地毯对红外辐射能发生散色与吸收, 导致误判 出现悬崖。 本发明实施例通过综合考虑反馈信号的能量大小以及反馈时长, 将 第二反馈信号小于第二检测阈值的情况进行预设等级划分, 分为确定悬崖等级 和待定悬崖等级。 比如反馈时间长、 同时反馈信号能量小, 为确定悬崖等级; 反馈时间短、 同时反馈信号能量小, 为待定悬崖等级。
[0070] 8361: 若为确定悬崖等级, 则判定上述第二探测地面为悬崖。
[0071] 参照图 7, 进一步地, 本发明再一实施例的悬崖检测方法中步骤 3360之后, 包 括:
[0072] 8362: 若为待定悬崖等级, 则启动辅助检测。
[0073] 本步骤中的辅助检测包括探测地面与机器人机身的物理高度、 地面材质形貌等 辅助判断手段, 以便从多维度推断结论的可靠性, 进一步提高准确度。
[0074] 8363: 根据上述辅助检测的检测结果判断上述差值是否在预判范围内。
[0075] 本步骤中的预判范围包括: 根据辅助检测的检测结果直接得出的判断结论。 比 如, 辅助检测中检测到第二探测地面的表面为长毛状白色羊毛地毯, 相比于标 准平坦白色地面上述差值偏小了 400至 500, 而偏小的 400至 500刚好为长毛状白 色羊毛地毯的吸收能力范围内, 则认为上述差值在预判范围内, 不是悬崖; 反 之, 则为悬崖。
[0076] 8364: 若不在, 则判定上述第二探测地面为悬崖。
[0077] 本发明又一实施例的悬崖检测方法, 上述步骤3362, 包括:
[0078] 83620: 通过超声波检测仪检测当前所处地面与上述第二探测地面间的高度差
[0079] 探测地面与机器人身体的物理高度通过辅助机械臂或超声波检测仪获得, 本实 施例优选安置于机器人机身底部的一个或多个超声波检测仪获得高度差辅助检 测信号。
[0080] 本发明又二实施例的悬崖检测方法, 上述步骤3362, 还包括: \¥0 2019/100403 卩(:17 \2017/113202
7
[0081] 83621: 通过材料检测仪检测上述第二探测地面的表面材质情况。
[0082] 本实施例优选安置于辅助机械臂末端的材料检测仪获取第二探测地面的表面材 质情况。
[0083] 参照图 8, 本发明一实施例的机器人, 包括:
[0084] 监测模块 1, 用于监测机器人移动过程中的地面的状态变化信息。
[0085] 本实施例的状态变化信息包括: 地面颜色的变化、 地面反射光强度变化、 地面 材质的变化等影响红外传感器悬崖检测的信息。 本实施例以机身头部底壳处安 装红外悬崖传感器的室内扫地机器人为例, 机器人在移动过程中实时监测地面 的状态变化信息。
[0086] 设置模块 2, 用于根据上述状态变化信息设置悬崖检测的限定条件。
[0087] 本实施例的红外悬崖传感器发送的红外检测信号对地面颜色等地面状态变化信 息比较敏感, 本实施例根据地面不同的状态变化信息, 动态设置悬崖检测的限 定条件, 以适合当前地面状态的红外线悬崖检测标准。 本实施例的限定条件为 预设的, 比如预先通过实验匹配不同颜色所对应的限定条件。 举例地, 红外线 的辐射信号对地面的颜色信息比较敏感, 检测黑色地面的信号值明显低于同距 离的白色地面的信号值; 当检测到地面状态变化信息由白色变为黑色, 则选择 黑色所对应的悬崖检测的限定条件本实施例将影响悬崖检测的干扰因素考虑在 内, 动态调控适合机器人当前地面状况的悬崖判断标准, 以提高判断悬崖的准 确度, 减少误判。
[0088] 判断模块 3 , 用于根据上述限定条件以及与上述限定条件对应的预设规则判断 探测地面是否为悬崖。
[0089] 本实施例中根据限定条件对应匹配预设规则, 以进一步提高判断悬崖的准确度 , 减少误判。 比如以地面颜色变化信息作为限定条件与以地面反射光强度变化 信息作为限定条件, 其所对应的判断悬崖的预设规则不同。
[0090] 参照图 9, 本发明另一实施例的机器人, 上述状态变化信息包括反射光强度变 化, 上述设置模块 2, 包括:
[0091] 第一监测单元 20, 用于监测第一探测地面的反射光强度与预设标准反射光强度 的强度差值。 [0092] 本实施例的地面反射光强度会影响红外传感器通过检测红外辐射能的变化量来 检测悬崖的判断, 比如, 反射光强度大的红外检测信号明显大于同距离的反射 光强度小的检测信号。 地面的反射光强度与地面的表面形貌、 材质以及地面与 检测器的距离等有关, 本实施例中预设标准反射光强度依据平坦表面状态的不 同材质而设, 通过第一探测地面的反射光强度与预设标准反射光强度的误差范 围可获知地面材质匹配信息, 并通过进一步监测第一探测地面的反射光强度与 预设标准反射光强度的强度差值, 来判断地面状态变化信息。
[0093] 第一判断单元 21, 用于根据上述强度差值判断是否需要更改上述限定条件。
[0094] 本实施例的反射光强度对应的红外线检测阈值会预先经过实验确定等级划分, 同等级范围内的误差波动, 比如地面的小幅度的凹凸不平带来的差值波动等, 则无需更改限定条件; 差值跨越等级时, 则需要变更红外线检测阈值。
[0095] 调用单元 22, 用于若判定是, 调用上述反射光强度对应的第一检测阈值。
[0096] 通过改变红外线检测阈值尽可能的除去不同反射光强度下检测悬崖的判断误差
[0097] 红外线检测悬崖通过比较发射波的反馈信号强度, 来判断是否有悬崖。
[0098] 参照图 10, 本发明另一实施例的机器人, 上述判断模块 3, 包括:
[0099] 第一发送单元 30, 用于向上述第一探测地面发送第一红外检测信号。
[0100] 本实施例中第一红外检测信号为红外悬崖传感器发送的红外辐射能信号。
[0101] 第一接收单元 31, 用于接收上述第一红外检测信号的第一反馈信号。
[0102] 第一反馈信号指红外辐射信号碰到障碍物后返回到红外悬崖传感器的辐射信号
[0103] 第二判断单元 32, 用于判断上述第一反馈信号是否小于上述第一检测阈值。
[0104] 本实施例中以指定地面反射光强度下, 无悬崖时的红外辐射能量的反馈信号强 度来确定第一检测阈值, 当第一反馈信号小于第一检测阈值时, 判定为悬崖, 若第一反馈信号不小于第一检测阈值时, 判定安全。
[0105] 第一判定单元 33 , 用于若上述第一反馈信号小于上述第一检测阈值, 则判定上 述第一探测地面为悬崖。
[0106] 参照图 11, 本发明再一实施例的机器人, 上述状态变化信息包括颜色变化, 上 \¥0 2019/100403 卩(:17 \2017/113202
9 述设置模块 2, 包括:
[0107] 第二监测单元 24, 用于监测第二探测地面的颜色。
[0108] 不同颜色对红外辐射光的吸收程度不同, 由于深颜色对红外辐射光的吸收程度 较高, 导致地面为黑色时, 红外辐射能信号的反馈信号值明显偏低, 甚至接收 不到反馈信号, 所以地面颜色对红外传感器检测悬崖的判断结果存在干扰。
[0109] 第三判断单元 25 , 用于判断是否存在与上述颜色匹配的第二检测阈值。
[0110] 本实施例预先通过实验匹配在不同纯颜色的无悬崖地面上的红外线检测阈值, 以便红外悬崖传感器在检测悬崖时根据不同地面颜色动态设置红外线检测阈值 , 以消除不同颜色对红外辐射能信号吸收率不同而导致的误差。
[0111] 设定单元 26, 用于若存在, 则设置小于上述第二检测阈值为悬崖检测的第二限 定条件。
[0112] 本实施例中以指定颜色地面, 无悬崖时的红外辐射能量反馈信号强度来确定第 二检测阈值, 当接收的反馈信号小于第二红外线检测时, 判定为悬崖。
[0113] 参照图 12, 本发明再一实施例的悬崖检测方法, 上述状态变化信息包括颜色变 化, 上述判断模块 3, 还包括:
[0114] 第二发送单元 34, 用于向上述第二探测地面发送第二红外检测信号。
[0115] 第二接收单元 35, 用于接收上述第二红外检测信号的第二反馈信号。
[0116] 第四判断单元 36 , 用于判断上述第二反馈信号是否小于上述第二检测阈值;
[0117] 第二判定单元 37, 用于若上述第二反馈信号不小于上述第二检测阈值, 则判定 机器人继续向前移动。
[0118] 本实施中的红外悬崖传感器检测原理同本发明另一实施例的相同, 只是红外线 检测阈值及其确定悬崖方法的预设规则不同。
[0119] 参照图 13, 进一步地, 本发明再一实施例的机器人上述判断模块 3, 包括:
[0120] 第五判断单元 360, 用于若上述第二反馈信号小于上述第二检测阈值, 则判断 上述第二反馈信号对应的预设等级, 上述预设等级包括确定悬崖等级和待定悬 崖等级。
[0121] 本实施例由于颜色对红外辐射能量的吸收率由较大差别、 而且地面材质及其形 貌也会同时影响地面对红外辐射能量的吸收率, 因此, 本实施例通过逐步判处 \¥0 2019/100403 卩(:17 \2017/113202
10 的方式, 进一步判定是否为悬崖, 提高准确度。 本实施例当第二反馈信号小于 第二检测阈值, 并不能直接判定为悬崖, 比如, 白色的长毛状地毯, 按照白色 设置第二检测阈值, 但长毛状的地毯对红外辐射能发生散色与吸收, 导致误判 出现悬崖。 本发明实施例通过综合考虑反馈信号的能量大小以及反馈时长, 将 第二反馈信号小于第二检测阈值的情况进行预设等级划分, 分为确定悬崖等级 和待定悬崖等级。 比如反馈时间长、 同时反馈信号能量小, 为确定悬崖等级; 反馈时间短、 同时反馈信号能量小, 为待定悬崖等级。
[0122] 第三判定单元 361, 用于若为确定悬崖等级, 则判定上述第二探测地面为悬崖
[0123] 参照图 14, 进一步地, 本发明再一实施例的机器人上述判断模块 3, 包括:
[0124] 启动单元 362, 用于若为待定悬崖等级, 则启动辅助检测。
[0125] 本实施例中的辅助检测包括探测地面与机器人机身的物理高度、 地面材质形貌 等辅助判断手段, 以便从多维度推断结论的可靠性, 进一步提高准确度。
[0126] 第六判断单元 363 , 用于根据上述辅助检测的检测结果判断上述差值是否在预 判范围内。
[0127] 本实施例中的预判范围包括: 根据辅助检测的检测结果直接得出的判断结论。
比如, 辅助检测中检测到第二探测地面的表面为长毛状白色羊毛地毯, 相比于 标准平坦白色地面上述差值偏小了 400至 500, 而偏小的 400至 500刚好为长毛状 白色羊毛地毯的吸收能力范围内, 则认为上述差值在预判范围内, 不是悬崖; 反之, 则为悬崖。
[0128] 第四判定单元 364, 用于若上述差值不在预判范围内, 则判定上述第二探测地 面为悬崖。
[0129] 参照图 15, 本发明又一实施例的机器人, 上述启动单元 362, 包括:
[0130] 第一检测子单元 3620, 用于通过超声波检测仪检测当前所处地面与上述第二探 测地面间的高度差。
[0131] 探测地面与机器人机身的物理高度通过辅助机械臂或超声波检测仪获得, 本实 施例优选安置于机器人机身底部的一个或多个超声波检测仪获得高度差辅助检 测信号。 \¥0 2019/100403 卩(:17 \2017/113202
11
[0132] 参照图 16, 本发明又二实施例的机器人, 上述启动单元 362, 还包括:
[0133] 第二检测子单元 3621, 用于通过材料检测仪检测上述第二探测地面的表面材质 情况。
[0134] 本实施例优选安置于辅助机械臂末端的材料检测仪获取第二探测地面的表面材 质情况。
[0135] 本发明实施例通过机器人通过监测所处地面的状态变化信息动态设置悬崖检测 的限定条件, 将影响悬崖检测的干扰因素考虑在内, 动态调控适合机器人当前 地面状况的悬崖判断标准, 细化不同地面状态下的悬崖检测的限定条件, 以提 高机器人判断悬崖的准确度, 减少误判。
[0136] 以上所述仅为本发明的优选实施例, 并非因此限制本发明的专利范围, 凡是 利用本发明说明书及附图内容所作的等效结构或等效流程变换, 或直接或间接 运用在其他相关的技术领域, 均同理包括在本发明的专利保护范围内。

Claims

\¥0 2019/100403 卩(:17 \2017/113202 12 权利要求书
[权利要求 1] 一种悬崖检测方法, 其特征在于, 包括:
监测机器人移动过程中的地面的状态变化信息; 根据所述状态变化信息设置悬崖检测的限定条件; 根据所述限定条件以及与所述限定条件对应的预设规则判断探测地面 是否为悬崖。
[权利要求 2] 根据权利要求 1所述的悬崖检测方法, 其特征在于, 所述状态变化信 息包括反射光强度变化, 所述根据所述状态变化信息设置悬崖检测的 限定条件的步骤, 包括:
监测第一探测地面的反射光强度与预设标准反射光强度的强度差值; 根据所述强度差值判断是否需要更改所述限定条件;
若判定是, 调用所述反射光强度对应的第一检测阈值。
[权利要求 3] 根据权利要求 2所述的悬崖检测方法, 其特征在于, 所述根据所述限 定条件以及与所述限定条件对应的预设规则判断探测地面是否为悬崖 的步骤, 包括:
向所述第一探测地面发送第一红外检测信号;
接收所述第一红外检测信号的第一反馈信号;
判断所述第一反馈信号是否小于所述第一检测阈值;
若所述第一反馈信号小于所述第一检测阈值, 则判定所述第一探测地 面为悬崖。
[权利要求 4] 根据权利要求 1所述的悬崖检测方法, 其特征在于, 所述状态变化信 息包括颜色变化, 所述根据所述状态变化信息设置悬崖检测的限定条 件的步骤, 包括:
监测第二探测地面的颜色;
判断是否存在与所述颜色匹配的第二检测阈值; 若存在, 则根据所述第二检测阈值设定悬崖检测的限定条件。
[权利要求 5] 根据权利要求 4所述的悬崖检测方法, 其特征在于, 所述根据所述限 定条件以及与所述限定条件对应的预设规则判断探测地面是否为悬崖 \¥0 2019/100403 卩(:17 \2017/113202
13 的步骤, 还包括:
向所述第二探测地面发送第二红外检测信号;
接收所述第二红外检测信号的第二反馈信号;
判断所述第二反馈信号是否小于所述第二检测阈值;
若所述第二反馈信号不小于所述第二检测阈值, 则判定机器人继续向 前移动。
[权利要求 6] 根据权利要求 5所述的悬崖检测方法, 其特征在于, 所述判断所述第 二反馈信号是否小于所述第二检测阈值的步骤之后, 包括: 若所述第二反馈信号小于所述第二检测阈值, 则判断所述第二反馈信 号对应的预设等级, 所述预设等级包括确定悬崖等级和待定悬崖等级 若为确定悬崖等级, 则判定所述第二探测地面为悬崖。
[权利要求 7] 根据权利要求 6所述的悬崖检测方法, 其特征在于, 所述若所述第二 反馈信号小于所述第二检测阈值, 则判断所述第二反馈信号对应的预 设等级, 所述预设等级包括确定悬崖等级和待定悬崖等级的步骤之后 , 包括:
若为待定悬崖等级, 则启动辅助检测;
根据所述辅助检测的检测结果判断所述差值是否在预判范围内; 若不在, 则判定所述第二探测地面为悬崖。
[权利要求 8] 根据权利要求 7所述的悬崖检测方法, 其特征在于, 所述启动辅助检 测的步骤, 包括:
通过超声波检测仪检测当前所处地面与所述第二探测地面间的高度差
[权利要求 9] 根据权利要求 7所述的悬崖检测方法, 其特征在于, 所述启动辅助检 测的步骤, 还包括:
通过材料检测仪检测所述第二探测地面的表面材质情况。
[权利要求 10] 一种机器人, 其特征在于, 包括:
监测模块, 用于监测机器人移动过程中的地面的状态变化信息; \¥0 2019/100403 卩(:17 \2017/113202
14 设置模块, 用于根据所述状态变化信息设置悬崖检测的限定条件; 判断模块, 用于根据所述限定条件以及与所述限定条件对应的预设规 则判断探测地面是否为悬崖。
[权利要求 11] 根据权利要求 10所述的机器人, 其特征在于, 所述状态变化信息包括 反射光强度变化, 所述设置模块, 包括:
第一监测单元, 用于监测第一探测地面的反射光强度与预设标准反射 光强度的强度差值;
第一判断单元, 用于根据所述差值判断是否需要更改所述限定条件; 调用单元, 用于若判定是, 调用所述反射光强度对应的第一检测阈值
[权利要求 12] 根据权利要求 11所述的机器人, 其特征在于, 所述判断模块, 包括: 第一发送单元, 用于向所述第一探测地面发送第一红外检测信号; 第一接收单元, 用于接收所述第一红外检测信号的第一反馈信号; 第二判断单元, 用于判断所述第一反馈信号是否小于所述第一检测阈 值;
第一判定单元, 用于若所述第一反馈信号小于所述第一检测阈值, 则 判定所述第一探测地面为悬崖。
[权利要求 13] 根据权利要求 10所述的机器人, 其特征在于, 所述状态变化信息包括 颜色变化, 所述设置模块, 包括:
第二监测单元, 用于监测第二探测地面的颜色; 第三判断单元, 用于判断是否存在与所述颜色匹配的第二检测阈值; 设定单元, 用于若存在, 则根据所述第二检测阈值设定悬崖检测的限 定条件。
[权利要求 14] 根据权利要求 13所述的机器人, 其特征在于, 所述判断模块, 还包括 第二发送单元, 用于向所述第二探测地面发送第二红外检测信号; 第二接收单元, 用于接收所述第二红外检测信号的第二反馈信号; 第四判断单元, 用于判断所述第二反馈信号是否小于所述第二检测阈 \¥0 2019/100403 卩(:17 \2017/113202
15 值;
第二判定单元, 用于若所述第二反馈信号不小于所述第二检测阈值, 则判定机器人继续向前移动。
[权利要求 15] 根据权利要求 14所述的机器人, 其特征在于, 所述判断模块, 包括: 第五判断单元, 用于若所述第二反馈信号小于所述第二检测阈值, 则 判断所述第二反馈信号对应的预设等级, 所述预设等级包括确定悬崖 等级和待定悬崖等级;
第三判定单元, 用于若为确定悬崖等级, 则判定所述第二探测地面为 悬崖。
[权利要求 16] 根据权利要求 15所述的机器人, 其特征在于, 所述判断模块, 包括: 启动单元, 用于若为待定悬崖等级, 则启动辅助检测;
第六判断单元, 用于根据所述辅助检测的检测结果判断所述差值是否 在预判范围内;
第四判定单元, 用于若所述差值不在预判范围内, 则判定所述第二探 测地面为悬崖。
[权利要求 17] 根据权利要求 16所述的机器人, 其特征在于, 所述启动单元, 包括: 第一检测子单元, 用于通过超声波检测仪检测当前所处地面与所述第 二探测地面间的高度差。
[权利要求 18] 根据权利要求 16所述的机器人, 其特征在于, 所述启动单元, 还包括 第二检测子单元, 用于通过材料检测仪检测所述第二探测地面的表面 材质情况
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